Literature DB >> 28817458

Noninvasive Derivation of Fractional Flow Reserve From Coronary Computed Tomographic Angiography: A Review.

Stewart M Benton1, Christian Tesche2,3, Carlo N De Cecco2, Taylor M Duguay2, U Joseph Schoepf1,2, Richard R Bayer1,2.   

Abstract

Coronary computed tomographic angiography (CCTA) has evolved as a rapid and highly sensitive method for the exclusion of obstructive coronary artery disease. Unfortunately, as it pertains to moderate and severe lesions, the ability to discriminate between those that are hemodynamically significant and those that are nonobstructive is lacking. Consequently, this deficiency can result in a significant number of unnecessary referrals for invasive angiography that yields nonobstructive results. Fractional flow reserve (FFR), which assesses the hemodynamic significance of a specific lesion, when performed during invasive angiography, results in improved patient outcomes compared with visual stenosis assessment alone. Through the application of computational analytic methods to CT-derived anatomic coronary models, noninvasive calculation of FFR has become possible. This allows for the improved ability to differentiate between nonobstructive coronary lesions and those that are truly hemodynamically significant. Currently, HeartFlow FFRCT is the only FDA-approved and commercially available CCTA-derived FFR (CT-FFR) platform. By reducing the number of invasive procedures performed for nonobstructive disease, CT-derived FFR has the ability to lower health care expenditures and become the true gatekeeper to invasive angiography.

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Year:  2018        PMID: 28817458     DOI: 10.1097/RTI.0000000000000289

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  9 in total

1.  Value of Machine Learning-based Coronary CT Fractional Flow Reserve Applied to Triple-Rule-Out CT Angiography in Acute Chest Pain.

Authors:  Simon S Martin; Domenico Mastrodicasa; Marly van Assen; Carlo N De Cecco; Richard R Bayer; Christian Tesche; Akos Varga-Szemes; Andreas M Fischer; Brian E Jacobs; Pooyan Sahbaee; L Parkwood Griffith; Andrew J Matuskowitz; Thomas J Vogl; U Joseph Schoepf
Journal:  Radiol Cardiothorac Imaging       Date:  2020-06-25

2.  Diagnostic accuracy of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) in patients before liver transplantation using CT-FFR machine learning algorithm.

Authors:  Maximilian Schuessler; Fuat Saner; Fadi Al-Rashid; Thomas Schlosser
Journal:  Eur Radiol       Date:  2022-06-22       Impact factor: 5.315

Review 3.  Understanding the predictive value and methods of risk assessment based on coronary computed tomographic angiography in populations with coronary artery disease: a review.

Authors:  Yiming Li; Kaiyu Jia; Yuheng Jia; Yong Yang; Yijun Yao; Mao Chen; Yong Peng
Journal:  Precis Clin Med       Date:  2021-07-26

4.  Impact of non-invasive anatomical testing on optimal medical prescription in patients with suspected coronary artery disease.

Authors:  Stijn Devuyst; Arno Gigase; Jerrold Spapen; Sofie Brouwers; Thomas Couck; Jeroen Sonck; Takuya Mizukami; Carlo Gigante; Herbert de Raedt; Dan Schelfaut; Ward Heggermont; Bernard De Bruyne; Martin Penicka; Guy Van Camp; Carlos Collet
Journal:  Cardiovasc Diagn Ther       Date:  2019-06

5.  Diagnostic performance of deep learning-based vascular extraction and stenosis detection technique for coronary artery disease.

Authors:  Meng Chen; Ximing Wang; Guangyu Hao; Xujie Cheng; Chune Ma; Ning Guo; Su Hu; Qing Tao; Feirong Yao; Chunhong Hu
Journal:  Br J Radiol       Date:  2020-03-25       Impact factor: 3.039

6.  CT Angiography-derived Fractional Flow Reserve: The Global Game of Thrones.

Authors:  U Joseph Schoepf; Hunter N Gray; Christian Tesche
Journal:  Radiol Cardiothorac Imaging       Date:  2019-10-31

7.  Novel radiomics features from CCTA images for the functional evaluation of significant ischaemic lesions based on the coronary fractional flow reserve score.

Authors:  Wenchao Hu; Xiangjun Wu; Di Dong; Long-Biao Cui; Min Jiang; Jibin Zhang; Yabin Wang; Xinjiang Wang; Lei Gao; Jie Tian; Feng Cao
Journal:  Int J Cardiovasc Imaging       Date:  2020-06-03       Impact factor: 2.357

8.  Additional Value of Machine-Learning Computed Tomographic Angiography-Based Fractional Flow Reserve Compared to Standard Computed Tomographic Angiography.

Authors:  Dirk Lossnitzer; Leonard Chandra; Marlon Rutsch; Tobias Becher; Daniel Overhoff; Sonja Janssen; Christel Weiss; Martin Borggrefe; Ibrahim Akin; Stefan Pfleger; Stefan Baumann
Journal:  J Clin Med       Date:  2020-03-03       Impact factor: 4.241

9.  Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve in Patients with Anomalous Origin of the Right Coronary Artery from the Left Coronary Sinus.

Authors:  Chun Xiang Tang; Meng Jie Lu; Joseph Uwe Schoepf; Christian Tesche; Maximilian Bauer; John Nance; Parkwood Griffith; Guang Ming Lu; Long Jiang Zhang
Journal:  Korean J Radiol       Date:  2020-02       Impact factor: 3.500

  9 in total

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